Brian Cervantes Alvarez

Summary

Statistician and data scientist with graduate training in both fields (M.S. Statistics, Oregon State; M.S. Data Science, Willamette) and applied experience across education, retail, and healthcare data.

Currently a Business Intelligence Analyst at the Oregon Department of Education, where I build dashboards and audited analytics over the state's educational data systems. Independent consulting via Epsilon Labs covers experimental design, predictive modeling, and decision- ready analytics for teams that need a scoped, defensible answer.

Experience

1. Dec 2025–Present

   Salem, OR

   Business Intelligence Analyst

   Oregon Department of Education

   • Designing dashboards and longitudinal reports that surface student-outcome trends across Oregon districts, used by program leads to prioritize interventions.
   • Modernizing the analytics layer over the agency's educational data systems — moving ad-hoc queries into versioned, auditable pipelines that produce the same numbers quarter over quarter.
   • Partnering with subject-matter experts to translate policy questions into statistically defensible analyses, with documented assumptions and limits.
2. 2024–Present

   Remote

   Principal · Statistical Consulting

   Epsilon Labs (independent)

   • Statistical consulting for teams that need scoped, defensible analytics — experimental design, predictive modeling, and interactive dashboards.
   • Engagements delivered on fixed-fee project or short-retainer terms, every one starting with a scoping call and a written proposal.
3. 2022–2024

   Corvallis, OR

   Graduate Researcher & Teaching Assistant

   Oregon State University · Department of Statistics

   • Modernized the department's data-visualization curriculum with Quarto, webR, and reproducible Shiny-based labs.
   • Taught undergraduate sections on regression, experimental design, and applied statistics; built lecture and lab materials still in use.
   • Research focus: Bayesian methods, missing-data imputation, and applied multivariate analysis.
4. 2021–2022

   Salem, OR

   Data Science Graduate Student

   Willamette University · MSDS

   • Capstone team projects spanning predictive modeling, ETL, and interactive dashboards on real datasets (retail, census, healthcare).
   • Earned the M.S. in Data Science with coursework in machine learning, reproducible analytics, and applied computing.

Education

• M.S. Statistics

  Oregon State University
  2024
• M.S. Data Science

  Willamette University
  2022
• B.S. Mathematics

  Linfield University
  2020

Full programs and coursework on the about page.

Capabilities

• Experimental design · A/B testing · power analysis
• Regression · GLMs · mixed-effects · Bayesian inference
• Classification · forecasting · time-to-event modeling
• Predictive ML · validation · explainability
• Interactive dashboards · self-service decision aids
• Reproducible pipelines · versioned · auditable
• Statistical training · workshops · curriculum design
• AI-native workflows · prompt engineering · model evaluation

Selected work

• UK Accident Time-Series Dashboard · interactive Shiny app over historical UK road-accident data.
• Wine Chemistry — Multivariate Analysis · MANOVA + classification on red vs. white at 99% accuracy.
• Yelp Reviews Spatial Dashboard · kriged surfaces and interactive variogram tuning for review data.
• Interactive Teaching with webR · browser-native R labs for cross-platform classrooms.

Speaking

Recent talks on logistic regression, MICE imputation, survival analysis, portfolio infrastructure, and webR in the classroom. Full list on the talks page.